Creation and Storage of Standards-based Pre-scanning Patient Questionnaires in PACS as DICOM Objects

Radiology departments around the country have completed the first evolution to digital imaging by becoming filmless. The next step in this evolution is to become truly paperless. Both patient and non-patient paperwork has to be eliminated in order for this transition to occur. A paper-based set of patient pre-scanning questionnaires were replaced with web-based forms for use in an outpatient imaging center. We discuss this process by which questionnaire elements are converted into SNOMED-CT terminology concepts, stored for future use, and sent to PACS in Digital Imaging and Communications in Medicine (DICOM) format to be permanently stored with the relevant study in the DICOM image database.     

cDNA基因芯片数据分析软件的研发进展

数据分析与挖掘是基因芯片研究的关键和难点,而软件是数据分析方法实现的主要手段。我们从以下几个方面对cDNA基因芯片分析软件进行了综述。首先介绍了芯片数据的获取及分析的软件,然后概述了不同统计软件在芯片数据分析中的应用,并详细介绍几种常用的芯片数据分析软件,最后简述了基因网络分析及数据挖掘方面的软件。     

RadMonitor: Radiology Operations Data Mining in Real Time

This paper describes the web-based visualization interface of RadMonitor, a platform-independent web application designed to help manage the complexity of information flow within a health care enterprise. The system eavesdrops on Health Layer 7 traffic and parses statistical operational information into a database. The information is then presented to the user as a treemap—a graphical visualization scheme that simplifies the display of hierarchical information. While RadMonitor has been implemented for the purpose of analyzing radiology operations, its XML backend allows it to be reused for virtually any other hierarchical data set.     

DW4TR: A Data Warehouse for Translational Research

The linkage between the clinical and laboratory research domains is a key issue in translational research. Integration of clinicopathologic data alone is a major task given the number of data elements involved. For a translational research environment, it is critical to make these data usable at the point-of-need. Individual systems have been developed to meet the needs of particular projects though the need for a generalizable system has been recognized. Increased use of Electronic Medical Record data in translational research will demand generalizing the system for integrating clinical data to support the study of a broad range of human diseases. To ultimately satisfy these needs, we have developed a system to support multiple translational research projects. This system, the Data Warehouse for Translational Research (DW4TR), is based on a light-weight, patient-centric modularly-structured clinical data model and a specimen-centric molecular data model. The temporal relationships of the data are also part of the model. The data are accessed through an interface composed of an Aggregated Biomedical-Information Browser (ABB) and an Individual Subject Information Viewer (ISIV) which target general users. The system was developed to support a breast cancer translational research program and has been extended to support a gynecological disease program. Further extensions of the DW4TR are underway. We believe that the DW4TR will play an important role in translational research across multiple disease types.     

Strategies for Medical Data Extraction and Presentation Part 2: Creating a Customizable Context and User-Specific Patient Reference Database

One of the greatest challenges facing healthcare professionals is the ability to directly and efficiently access relevant data from the patient’s healthcare record at the point of care; specific to both the context of the task being performed and the specific needs and preferences of the individual end-user. In radiology practice, the relative inefficiency of imaging data organization and manual workflow requirements serves as an impediment to historical imaging data review. At the same time, clinical data retrieval is even more problematic due to the quality and quantity of data recorded at the time of order entry, along with the relative lack of information system integration. One approach to address these data deficiencies is to create a multi-disciplinary patient referenceable database which consists of high-priority, actionable data within the cumulative patient healthcare record; in which predefined criteria are used to categorize and classify imaging and clinical data in accordance with anatomy, technology, pathology, and time. The population of this referenceable database can be performed through a combination of manual and automated methods, with an additional step of data verification introduced for data quality control. Once created, these referenceable databases can be filtered at the point of care to provide context and user-specific data specific to the task being performed and individual end-user requirements.     

An Automated DICOM Database Capable of Arbitrary Data Mining (Including Radiation Dose Indicators) for Quality Monitoring

The U.S. National Press has brought to full public discussion concerns regarding the use of medical radiation, specifically x-ray computed tomography (CT), in diagnosis. A need exists for developing methods whereby assurance is given that all diagnostic medical radiation use is properly prescribed, and all patients’ radiation exposure is monitored. The “DICOM Index Tracker©” (DIT) transparently captures desired digital imaging and communications in medicine (DICOM) tags from CT, nuclear imaging equipment, and other DICOM devices across an enterprise. Its initial use is recording, monitoring, and providing automatic alerts to medical professionals of excursions beyond internally determined trigger action levels of radiation. A flexible knowledge base, aware of equipment in use, enables automatic alerts to system administrators of newly identified equipment models or software versions so that DIT can be adapted to the new equipment or software. A dosimetry module accepts mammography breast organ dose, skin air kerma values from XA modalities, exposure indices from computed radiography, etc. upon receipt. The American Association of Physicists in Medicine recommended a methodology for effective dose calculations which are performed with CT units having DICOM structured dose reports. Web interface reporting is provided for accessing the database in real-time. DIT is DICOM-compliant and, thus, is standardized for international comparisons. Automatic alerts currently in use include: email, cell phone text message, and internal pager text messaging. This system extends the utility of DICOM for standardizing the capturing and computing of radiation dose as well as other quality measures.Key words: Data extraction, medical informatics applications, radiation dose, database management systems, knowledge base     

Strategies for Medical Data Extraction and Presentation Part 3: Automated Context- and User-Specific Data Extraction

In current medical practice, data extraction is limited by a number of factors including lack of information system integration, manual workflow, excessive workloads, and lack of standardized databases. The combined limitations result in clinically important data often being overlooked, which can adversely affect clinical outcomes through the introduction of medical error, diminished diagnostic confidence, excessive utilization of medical services, and delays in diagnosis and treatment planning. Current technology development is largely inflexible and static in nature, which adversely affects functionality and usage among the diverse and heterogeneous population of end users. In order to address existing limitations in medical data extraction, alternative technology development strategies need to be considered which incorporate the creation of end user profile groups (to account for occupational differences among end users), customization options (accounting for individual end user needs and preferences), and context specificity of data (taking into account both the task being performed and data subject matter). Creation of the proposed context- and user-specific data extraction and presentation templates offers a number of theoretical benefits including automation and improved workflow, completeness in data search, ability to track and verify data sources, creation of computerized decision support and learning tools, and establishment of data-driven best practice guidelines.     

Tracking PACS Usage with Open Source Tools

A typical choice faced by Picture Archiving and Communication System (PACS) administrators is deciding how many PACS workstations are needed and where they should be sited. Oftentimes, the social consequences of having too few are severe enough to encourage oversupply and underutilization. This is costly, at best in terms of hardware and electricity, and at worst (depending on the PACS licensing and support model) in capital costs and maintenance fees. The PACS administrator needs tools to asses accurately the use to which her fleet is being subjected, and thus make informed choices before buying more workstations. Lacking a vended solution for this challenge, we developed our own.     

Focused Decision Support: a Data Mining Tool to Query the Prostate,Lung, Colorectal,and Ovarian Cancer Screening Trial Dataset and Guide Screening Management for the Individual Patient

The Prostate, Lung, Colorectal, and Ovarian Cancer (PLCO) Screening Trial enrolled ~155,000 participants to determine whether certain screening exams reduced mortality from prostate, lung, colorectal, and ovarian cancer. Repurposing the data provides an unparalleled resource for matching patients with the outcomes of demographically or diagnostically comparable patients. A web-based application was developed to query this subset of patient information against a given patient’s demographics and risk factors. Analysis of the matched data yields outcome information which can then be used to guide management decisions and imaging software. Prognostic information is also estimated via the proportion of matched patients that progress to cancer. The US Preventative Services Task Force provides screening recommendations for cancers of the breast, colorectal tract, and lungs. There is wide variability in adherence of clinicians to these guidelines and others published by the Fleischner Society and various cancer organizations. Data mining the PLCO dataset for clinical decision support can optimize the use of limited healthcare resources, focusing screening on patients for whom the benefit to risk ratio is the greatest and most efficacious. A data driven, personalized approach to cancer screening maximizes the economic and clinical efficacy and enables early identification of patients in which the course of disease can be improved. Our dynamic decision support system utilizes a subset of the PLCO dataset as a reference model to determine imaging and testing appropriateness while offering prognostic information for various cancers.     

基于数据挖掘分析GPR35表达对肺腺癌预后的影响

研究数据挖掘分析GPR35表达对肺腺癌预后的影响,并明晰其参与的分析调控网络。方法 利用Oncomine数据库挖掘GPR35在肺腺癌组织中的表达情况;利用Kaplan-Meier Plotter进行肺腺癌患者生存周期分析;利用Coexpedia数据库分析GPR35参与的分子调控网络。结果 GPR35在人体正常组织中均有表达,其中胰腺组织和骨髓来源的CD33+细胞含量较高。相比于正常肺组织,GPR35基因在肺腺癌组织中呈现高表达,而在肺鳞癌以及大细胞肺癌中,未见明显变化。GPR35基因在肺腺癌组织中,男性患者相对于女性患者呈现高表达,而其表达在StageⅠ和StageⅣ均明显上调,且StageⅣ中GPR35的表达高于其他三期的患者;肺腺癌组织中存在EGFR L858R突变的患者,其GPR35的表达相对于无突变的患者明显上调。GPR35的表达水平对肺腺癌患者的总生存时间有着显著影响。与低表达组相比,GPR35高表达组肺腺癌患者的总存活时间降低（P＜0.05）;GPR35的表达水平对LUSC患者的总生存时间未见显著影响（P＞0.05）。GPR35参与多种肿瘤相关的分子调控网络。结论 大样本数据挖掘能迅速准确地获取肺腺癌组织中GPR35表达的相关信息,为深入研究奠定基础。     

基于数据挖掘的罗秀丽教授治疗三阴性乳腺癌的临床经验研究

目的 借助数据挖掘方法,客观总结罗秀丽教授中医药治疗三阴性乳腺癌的临床经验。方法 以罗秀丽教授2018年1月~12月收治的三阴乳腺癌患者68例为资料建立数据库,借助中医传承辅助平台（V2.5）的数据挖掘技术分析患者的年龄、证型、中药四气五味归经的分布与用药的关联规律。结果 患者年龄主要集中在40~69岁（77.94%）,证型以肝郁气滞证和脾虚痰湿证为主;用药频次前3位的依次为甘草、鳖甲、猪殃殃;治法以清热解毒为主,用药以平、温、微寒为主,少用大寒大热之品。置信度最高的药对为猪殃殃和鳖甲,置信度最高的药组为天葵子、猪殃殃、鳖甲。结论 罗秀丽教授认为乳岩多与肝脾二脏有关,治疗上多以清热解毒为主,用药时注重顾护脾胃,以甘平为主,擅长用药对、药组。     

适用于检测生理信号的高精度光隔离数据转换卡

作者针对目前常见数据转换卡对低频小信号传输性能较差的缺陷，介绍了一种适用于检测生理信号，可与ＰＣ机及其兼容机直接接口，带光隔离脉冲调制电路的高精度数据转换卡。简述其原理、构成及应用。电路具有七路输入选通１２位Ａ／Ｄ转换及两路８位Ｄ／Ａ输出，采用高频脉冲调制技术，实现了对多路模拟低频或直接生理小信号的光电传输，能够满足智能化医疗仪器中对各种生理信号测量、分析、诊断的需要，该转换卡使用方便、通用性强，     

DICOM for Clinical Research: PACS-Integrated Electronic Data Capture in Multi-Center Trials

Providing surrogate endpoints in clinical trials, medical imaging has become increasingly important in human-centered research. Nowadays, electronic data capture systems (EDCS) are used but binary image data is integrated insufficiently. There exists no structured way, neither to manage digital imaging and communications in medicine (DICOM) data in EDCS nor to interconnect EDCS with picture archiving and communication systems (PACS). Manual detours in the trial workflow yield errors, delays, and costs. In this paper, requirements for a DICOM-based system interconnection of EDCS and research PACS are analysed. Several workflow architectures are compared. Optimized for multi-center trials, we propose an entirely web-based solution integrating EDCS, PACS, and DICOM viewer, which has been implemented using the open source projects OpenClinica, DCM4CHEE, and Weasis, respectively. The EDCS forms the primary access point. EDCS to PACS interchange is integrated seamlessly on the data and the context levels. DICOM data is viewed directly from the electronic case report form (eCRF), while PACS-based management is hidden from the user. Data privacy is ensured by automatic de-identification and re-labelling with study identifiers. Our concept is evaluated on a variety of 13 DICOM modalities and transfer syntaxes. We have implemented the system in an ongoing investigator-initiated trial (IIT), where five centers have recruited 24 patients so far, performing decentralized computed tomography (CT) screening. Using our system, the chief radiologist is reading DICOM data directly from the eCRF. Errors and workflow processing time are reduced. Furthermore, an imaging database is built that may support future research.     

GeneSifter在基因表达谱芯片数据挖掘中的应用

介绍一款基因芯片数据分析工具——GeneSifter软件。具有快速、直观、便捷等特点，尤其适用于基因表达谱的数据挖掘。芯片数据一般以格式化文本文档形式上载，根据实验目的、设计不同，总共有4种上载向导工具，数据分析从控制台Analysis项目下的Pairwise或Projects进入，需要设置滤过、阈值和统计分析等参数，Pairwise可获得的结果有：差异显著性基因列表、基因本体报告和KEGG通路报告等，Projects有更为强大的功能，可获取聚类等6种结果。GeneSifter独特的一站式单击设置，可获得相关基因的11个数据库最新链接。GeneSifcer适用于基因芯片数据挖掘的生物研究人员。     

医院备份系统解决方案

我们介绍了一个医院数据备份系统方案。分析了备份系统方案的设计目标 :对医院业务系统和数据库建立一个集中管理的、自动化的、高速有效的备份手段     

Association between Statin Use and Cancer: Data Mining of a Spontaneous Reporting Database and a Claims Database

Purpose: In recent years, the potential risk of cancer associated with statin use has been a focus of much interest. However, it remains uncertain whether statin therapy is associated with cancer risk. To examine the association between statin use and the risk of cancer, we conducted data mining using the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) and a large organized database of claims constructed by a database vendor (The Japan Medical Data Center Co., Ltd, Tokyo, Japan [JMDC]).Methods: Relevant reports in the FAERS, which included data from the first quarter of 2004 through the end of 2012, were identified and analyzed. The reporting odds ratio (ROR) was used to detect spontaneous report signals and was calculated using the case/non-case method. Additionally, signals were detected via the information component (IC) using the IC025 metric. Furthermore, event sequence symmetry analysis (ESSA) was applied to identify the risk of cancer following treatment with statins over the period January 2005 to July 2013.Results: In the FAERS database analyses, significant signals for colorectal cancer and pancreatic cancer were found for statins as a class. In the ESSA, significant associations between statin use and colorectal cancer and pancreatic cancer were found, with adjusted sequence ratios (95% confidence intervals) of 1.20 (1.08-1.34) and 1.31 (1.13-1.53), respectively, at an interval of 48 months.Conclusions: Multi-methodological approaches using different algorithms and databases suggest that statin use is associated with an increased risk for colorectal cancer and pancreatic cancer.     

Data management plans: the missing perspective

The National Institutes of Health requires data sharing plans for projects with over five hundred thousand dollars in direct costs in a single year and has recently released a new guidance on rigor and reproducibility in grant applications. The National Science Foundation outright requires Data Management Plans (DMPs) as part of applications for funding. However, there is no general and definitive list of topics that should be covered in a DMP for a research project. We identified and reviewed DMP requirements from research funders. Forty-three DMP topics were identified. The review uncovered inconsistent requirements for written DMPs as well as high variability in required or suggested DMP topics among funder requirements. DMP requirements were found to emphasize post-publication data sharing rather than upstream activities that impact data quality, provide traceability or support reproducibility. With the emphasis equalized, the forty-three identified topics can aid Data Managers in systematically generating comprehensive DMPs that support research project planning and funding application evaluation as well as data management conduct and post-publication data sharing.     

Data mining of clinical oral health documents for analysis of the longevity of different restorative materials in Finland

Evidence-based dentistry has shown that different restorative materials have different survival times. Our primary hypothesis is that this should be revealed from normal dental records by the use of data mining technique and a practice-based dentistry approach analysed in a scientifically sound way. Dental records from 1626 patients and altogether 19,892 restorations in three Finnish age cohorts were analysed. Survival curves (Kaplan-Meier) were drawn for each of the restorative materials. Median survival times for amalgam and resin-based composites were more than 15 years in older cohorts. More than 60% of silicate cement restorations were replaced within 5 years, and more than 50% of glass ionomers within 7 years. There was a significant reduction in the longevity of amalgams in the 1980 cohort. Data mining of digital oral heath documents would be a useful tool to analyse survival curves of new restorative materials in a practice-based manner in real-life conditions.